Evidence map›Paper›PMID 36113527›Full record

ArticleThe Lancet. Global health2022

Feasibility of measles and rubella vaccination programmes for disease elimination: a modelling study.

Amy K Winter, Brian Lambert, Daniel Klein, Petra Klepac, Timos Papadopoulos, Shaun Truelove, Colleen Burgess, Heather Santos, Jennifer K Knapp, Susan E Reef and 8 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 38 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 11 institutions in 4 countries.

Amy K WinterDepartment of Epidemiology and Biostatics and Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA. Electronic address: awinter@uga.edu.
Brian LambertDepartment of Biology, Pennsylvania State University, State College, PA, USA.
Daniel KleinInstitute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, WA, USA.
Petra KlepacDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Timos PapadopoulosDepartment of Statistics Modelling and Economics, UK Health Security Agency, London, UK; Institute of Sound and Vibration Research, University of Southampton, Southampton, UK.
Shaun TrueloveDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Colleen BurgessRamboll Health Sciences, Copenhagen, Denmark.
Heather SantosDepartment of Biology, Pennsylvania State University, State College, PA, USA.
Jennifer K KnappGlobal Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Susan E ReefGlobal Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Lidia K KayembeGlobal Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Stephanie ShendaleDepartment of Immunization, Vaccines and Biologicals, WHO, Geneva, Switzerland.
Katrina KretsingerDepartment of Immunization, Vaccines and Biologicals, WHO, Geneva, Switzerland.
Justin LesslerDepartment of Epidemiology, Gillings School of Global Public Health and Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA.
Emilia VynnyckyDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK; TB Modelling Group, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Statistics Modelling and Economics, UK Health Security Agency, London, UK.
Kevin McCarthyInstitute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, WA, USA.
Matthew FerrariDepartment of Biology, Pennsylvania State University, State College, PA, USA.
Mark JitDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Centers for Disease Control and Prevention · USLondon School of Hygiene & Tropical Medicine · GBPennsylvania State University · USWorld Health Organization · CHBill & Melinda Gates Foundation · USInstitute for Disease Modeling · USJohns Hopkins University · USRamboll (Denmark) · DKUniversity of Georgia · USUniversity of North Carolina at Chapel Hill · USUniversity of Southampton · GB

Funding

CDC HHSIntramural CDC HHS CC999999World Health Organization 001
6 · The paper itself

Abstract

backgroundMarked reductions in the incidence of measles and rubella have been observed since the widespread use of the measles and rubella vaccines. Although no global goal for measles eradication has been established, all six WHO regions have set measles elimination targets. However, a gap remains between current control levels and elimination targets, as shown by large measles outbreaks between 2017 and 2019. We aimed to model the potential for measles and rubella elimination globally to inform a WHO report to the 73rd World Health Assembly on the feasibility of measles and rubella eradication.

methodsIn this study, we modelled the probability of measles and rubella elimination between 2020 and 2100 under different vaccination scenarios in 93 countries of interest. We evaluated measles and rubella burden and elimination across two national transmission models each (Dynamic Measles Immunisation Calculation Engine [DynaMICE], Pennsylvania State University [PSU], Johns Hopkins University, and Public Health England models), and one subnational measles transmission model (Institute for Disease Modeling model). The vaccination scenarios included a so-called business as usual approach, which continues present vaccination coverage, and an intensified investment approach, which increases coverage into the future. The annual numbers of infections projected by each model, country, and vaccination scenario were used to explore if, when, and for how long the infections would be below a threshold for elimination.

findingsThe intensified investment scenario led to large reductions in measles and rubella incidence and burden. Rubella elimination is likely to be achievable in all countries and measles elimination is likely in some countries, but not all. The PSU and DynaMICE national measles models estimated that by 2050, the probability of elimination would exceed 75% in 14 (16%) and 36 (39%) of 93 modelled countries, respectively. The subnational model of measles transmission highlighted inequity in routine coverage as a likely driver of the continuance of endemic measles transmission in a subset of countries.

interpretationTo reach regional elimination goals, it will be necessary to innovate vaccination strategies and technologies that increase spatial equity of routine vaccination, in addition to investing in existing surveillance and outbreak response programmes.

fundingWHO, Gavi, the Vaccine Alliance, US Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation.

Indexed as

MeaslesRubellaDisease EradicationFeasibility StudiesHumansUnited StatesVaccination

Identifiers

PMID36113527
PMCPMC9557212
OpenAlexW4296160974

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.